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Economic Growth, CO2 Emissions Quota and Optimal Allocation under Uncertainty
This study attempts to link greenhouse gas emissions and economic development, and under the premise of considering economic development, proposes an optimal quota of greenhouse gas emissions. Based on the environmental Kuznets curve hypothesis, the logarithmic value of greenhouse gas emissions is an inverted U-shaped function of the logarithmic value of GDP per capita. The empirical results showed that most countries in the world support the Kuznets curve hypothesis. Moreover, using data collected from Our World in Data, the optimal allocation of a greenhouse gas emissions quota can be found by minimizing the uncertainty risk subject to a prespecified global economic growth rate. For government policymakers, they may apply the framework in this study to determine an optimal allocation of greenhouse gas emissions for each sector that will ensure the intended level of domestic economic growth.
Economic Growth, CO2 Emissions Quota and Optimal Allocation under Uncertainty
This study attempts to link greenhouse gas emissions and economic development, and under the premise of considering economic development, proposes an optimal quota of greenhouse gas emissions. Based on the environmental Kuznets curve hypothesis, the logarithmic value of greenhouse gas emissions is an inverted U-shaped function of the logarithmic value of GDP per capita. The empirical results showed that most countries in the world support the Kuznets curve hypothesis. Moreover, using data collected from Our World in Data, the optimal allocation of a greenhouse gas emissions quota can be found by minimizing the uncertainty risk subject to a prespecified global economic growth rate. For government policymakers, they may apply the framework in this study to determine an optimal allocation of greenhouse gas emissions for each sector that will ensure the intended level of domestic economic growth.
Economic Growth, CO2 Emissions Quota and Optimal Allocation under Uncertainty
Chiu-Ming Hsiao (author)
2022
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
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